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【专知荟萃25】文字识别OCR知识资料全集（入门/进阶/论文/综述/代码/专家，附查看）

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OCR文字，车牌，验证码识别专知荟萃

入门学习
论文及代码

文字识别
文字检测
验证码破解
手写体识别
车牌识别

实战项目
视频

入门学习

端到端的OCR：基于CNN的实现

blog: [http://blog.xlvector.net/2016-05/mxnet-ocr-cnn/]

如何用卷积神经网络CNN识别手写数字集？

blog: [http://www.cnblogs.com/charlotte77/p/5671136.html]

OCR文字识别用的是什么算法？

[https://www.zhihu.com/question/20191727]

基于计算机视觉/深度学习打造先进OCR工作流 Creating a Modern OCR Pipeline Using Computer Vision and Deep Learning

[https://blogs.dropbox.com/tech/2017/04/creating-a-modern-ocr-pipeline-using-computer-vision-and-deep-learning/]

车牌识别中的不分割字符的端到端(End-to-End)识别

[http://m.blog.csdn.net/Relocy/article/details/52174198]

端到端的OCR：基于CNN的实现

[http://blog.xlvector.net/2016-05/mxnet-ocr-cnn/]

腾讯OCR—自动识别技术，探寻文字真实的容颜

[http://blog.xlvector.net/2016-05/mxnet-ocr-cnn/]

Tesseract-OCR引擎入门

[http://blog.csdn.net/xiaochunyong/article/details/7193744]

汽车挡风玻璃VIN码识别

[https://github.com/DoctorDYL/VINOCR]

车牌识别算法的关键技术及其研究现状

[http://www.siat.cas.cn/xscbw/xsqk/201012/W020101222564768411838.pdf]

端到端的OCR：验证码识别

[https://zhuanlan.zhihu.com/p/21344595?refer=xlvector]

论文及代码

文字识别

Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

intro: Google. Ian J. Goodfellow
arxiv: [https://arxiv.org/abs/1312.6082]

End-to-End Text Recognition with Convolutional Neural Networks

paper: [http://www.cs.stanford.edu/~acoates/papers/wangwucoatesng_icpr2012.pdf]
PhD thesis: [http://cs.stanford.edu/people/dwu4/HonorThesis.pdf]

Word Spotting and Recognition with Embedded Attributes

paper: [http://ieeexplore.ieee.org.sci-hub.org/xpl/articleDetails.jsp?arnumber=6857995&filter%3DAND%28p_IS_Number%3A6940341%29]

Reading Text in the Wild with Convolutional Neural Networks

arxiv: [http://arxiv.org/abs/1412.1842]
homepage: [http://www.robots.ox.ac.uk/~vgg/publications/2016/Jaderberg16/]
demo: [http://zeus.robots.ox.ac.uk/textsearch/#/search/]
code: [http://www.robots.ox.ac.uk/~vgg/research/text/]

Deep structured output learning for unconstrained text recognition

arxiv: [http://arxiv.org/abs/1412.5903]

Deep Features for Text Spotting

paper: [http://www.robots.ox.ac.uk/~vgg/publications/2014/Jaderberg14/jaderberg14.pdf]
bitbucket: [https://bitbucket.org/jaderberg/eccv2014_textspotting]
gitxiv: [http://gitxiv.com/posts/uB4y7QdD5XquEJ69c/deep-features-for-text-spotting]

Reading Scene Text in Deep Convolutional Sequences

arxiv: [http://arxiv.org/abs/1506.04395]

DeepFont: Identify Your Font from An Image

arxiv: [http://arxiv.org/abs/1507.03196]

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

intro: Convolutional Recurrent Neural Network
arxiv: [http://arxiv.org/abs/1507.05717]
github: [https://github.com/bgshih/crnn]
github: [https://github.com/meijieru/crnn.pytorch]

Recursive Recurrent Nets with Attention Modeling for OCR in the Wild

arxiv: [http://arxiv.org/abs/1603.03101]

Writer-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networks

arxiv: [http://arxiv.org/abs/1604.00974]

DeepText: A Unified Framework for Text Proposal Generation and Text Detection in Natural Images

arxiv: [http://arxiv.org/abs/1605.07314]

End-to-End Interpretation of the French Street Name Signs Dataset

paper: [http://link.springer.com/chapter/10.1007%2F978-3-319-46604-0_30]
github: [https://github.com/tensorflow/models/tree/master/street]

End-to-End Subtitle Detection and Recognition for Videos in East Asian Languages via CNN Ensemble with Near-Human-Level Performance

arxiv: [https://arxiv.org/abs/1611.06159]

Smart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Reading

arxiv: [https://arxiv.org/abs/1611.07385]

Improving Text Proposals for Scene Images with Fully Convolutional Networks

intro: Universitat Autonoma de Barcelona & University of Florence
intro: International Conference on Pattern Recognition - DLPR workshop
arxiv: [https://arxiv.org/abs/1702.05089]

Scene Text Eraser

[https://arxiv.org/abs/1705.02772]

Attention-based Extraction of Structured Information from Street View Imagery

intro: University College London & Google Inc
arxiv: [https://arxiv.org/abs/1704.03549]
github: [https://github.com/tensorflow/models/tree/master/attention_ocr]

STN-OCR: A single Neural Network for Text Detection and Text Recognition

arxiv: [https://arxiv.org/abs/1707.08831]
github: [https://github.com/Bartzi/stn-ocr]

Sequence to sequence learning for unconstrained scene text recognition

intro: master thesis
arxiv: [http://arxiv.org/abs/1607.06125]

Drawing and Recognizing Chinese Characters with Recurrent Neural Network

arxiv: [https://arxiv.org/abs/1606.06539]

Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition

intro: correct rates: Dataset-CASIA 97.10% and Dataset-ICDAR 97.15%
arxiv: [https://arxiv.org/abs/1610.02616]

Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Chinese Character Recognition

arxiv: [https://arxiv.org/abs/1610.04057]

Visual attention models for scene text recognition

[https://arxiv.org/abs/1706.01487]

Focusing Attention: Towards Accurate Text Recognition in Natural Images

intro: ICCV 2017
arxiv: [https://arxiv.org/abs/1709.02054]

Scene Text Recognition with Sliding Convolutional Character Models

[https://arxiv.org/abs/1709.01727]

AdaDNNs: Adaptive Ensemble of Deep Neural Networks for Scene Text Recognition

[https://arxiv.org/abs/1710.03425]

A New Hybrid-parameter Recurrent Neural Networks for Online Handwritten Chinese Character Recognition

[https://arxiv.org/abs/1711.02809]

Arbitrarily-Oriented Text Recognition

intro: A method used in ICDAR 2017 word recognition competitions
arxiv: [https://arxiv.org/abs/1711.04226]

文字检测

Object Proposals for Text Extraction in the Wild

intro: ICDAR 2015
arxiv: [http://arxiv.org/abs/1509.02317]
github: [https://github.com/lluisgomez/TextProposals]

Text-Attentional Convolutional Neural Networks for Scene Text Detection

arxiv: [http://arxiv.org/abs/1510.03283]

Accurate Text Localization in Natural Image with Cascaded Convolutional Text Network

arxiv: [http://arxiv.org/abs/1603.09423]

Synthetic Data for Text Localisation in Natural Images

intro: CVPR 2016
project page: [http://www.robots.ox.ac.uk/~vgg/data/scenetext/]
arxiv: [http://arxiv.org/abs/1604.06646]
paper: [http://www.robots.ox.ac.uk/~vgg/data/scenetext/gupta16.pdf]
github: [https://github.com/ankush-me/SynthText]

Scene Text Detection via Holistic, Multi-Channel Prediction

arxiv: [http://arxiv.org/abs/1606.09002]

Detecting Text in Natural Image with Connectionist Text Proposal Network

intro: ECCV 2016
arxiv: [http://arxiv.org/abs/1609.03605]
github: [https://github.com/tianzhi0549/CTPN]
github: [https://github.com/qingswu/CTPN]
demo: [http://textdet.com/]
github: [https://github.com/eragonruan/text-detection-ctpn]

TextBoxes: A Fast Text Detector with a Single Deep Neural Network

intro: AAAI 2017
arxiv: [https://arxiv.org/abs/1611.06779]
github: [https://github.com/MhLiao/TextBoxes]
github: [https://github.com/xiaodiu2010/TextBoxes-TensorFlow]

Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection

intro: CVPR 2017
intro: F-measure 70.64%, outperforming the existing state-of-the-art method with F-measure 63.76%
arxiv: [https://arxiv.org/abs/1703.01425]

Detecting Oriented Text in Natural Images by Linking Segments

intro: CVPR 2017
arxiv: [https://arxiv.org/abs/1703.06520]
github: [https://github.com/dengdan/seglink]

Deep Direct Regression for Multi-Oriented Scene Text Detection

arxiv: [https://arxiv.org/abs/1703.08289]

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

[https://arxiv.org/abs/1704.00834]

WordFence: Text Detection in Natural Images with Border Awareness

intro: ICIP 2017
arcxiv: [https://arxiv.org/abs/1705.05483]

SSD-text detection: Text Detector

intro: A modified SSD model for text detection
github: [https://github.com/oyxhust/ssd-text_detection]

R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection

intro: Samsung R&D Institute China
arxiv: [https://arxiv.org/abs/1706.09579]

R-PHOC: Segmentation-Free Word Spotting using CNN

intro: ICDAR 2017
arxiv: [https://arxiv.org/abs/1707.01294]

Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks

[https://arxiv.org/abs/1707.03985]

EAST: An Efficient and Accurate Scene Text Detector

intro: CVPR 2017
arxiv: [https://arxiv.org/abs/1704.03155]
github: [https://github.com/argman/EAST]

Deep Scene Text Detection with Connected Component Proposals

intro: Amap Vision Lab, Alibaba Group
arxiv: [https://arxiv.org/abs/1708.05133]

Single Shot Text Detector with Regional Attention

intro: ICCV 2017
arxiv: [https://arxiv.org/abs/1709.00138]
github: [https://github.com/BestSonny/SSTD]
code: [http://sstd.whuang.org]

Fused Text Segmentation Networks for Multi-oriented Scene Text Detection

[https://arxiv.org/abs/1709.03272]

Deep Residual Text Detection Network for Scene Text

intro: IAPR International Conference on Document Analysis and Recognition 2017. Samsung R&D Institute of China, Beijing
arxiv: [https://arxiv.org/abs/1711.04147]

Feature Enhancement Network: A Refined Scene Text Detector

intro: AAAI 2018
arxiv: [https://arxiv.org/abs/1711.04249]

ArbiText: Arbitrary-Oriented Text Detection in Unconstrained Scene

[https://arxiv.org/abs/1711.11249]

验证码破解

Using deep learning to break a Captcha system

intro: "Using Torch code to break simplecaptcha with 92% accuracy"
blog: [https://deepmlblog.wordpress.com/2016/01/03/how-to-break-a-captcha-system/]
github: [https://github.com/arunpatala/captcha]

Breaking reddit captcha with 96% accuracy

blog: [https://deepmlblog.wordpress.com/2016/01/05/breaking-reddit-captcha-with-96-accuracy/]
github: [https://github.com/arunpatala/reddit.captcha]

I’m not a human: Breaking the Google reCAPTCHA

paper: [https://www.blackhat.com/docs/asia-16/materials/asia-16-Sivakorn-Im-Not-a-Human-Breaking-the-Google-reCAPTCHA-wp.pdf]

Neural Net CAPTCHA Cracker

slides: [http://www.cs.sjsu.edu/faculty/pollett/masters/Semesters/Spring15/geetika/CS298%20Slides%20-%20PDF]
github: [https://github.com/bgeetika/Captcha-Decoder]
demo: [http://cp-training.appspot.com/]

Recurrent neural networks for decoding CAPTCHAS

blog: [https://deepmlblog.wordpress.com/2016/01/12/recurrent-neural-networks-for-decoding-captchas/]
demo: [http://simplecaptcha.sourceforge.net/]
code: [http://sourceforge.net/projects/simplecaptcha/]

Reading irctc captchas with 95% accuracy using deep learning

github: [https://github.com/arunpatala/captcha.irctc]

I Am Robot: Learning to Break Semantic Image CAPTCHAs

intro: automatically solving 70.78% of the image reCaptchachallenges, while requiring only 19 seconds per challenge. apply to the Facebook image captcha and achieve an accuracy of 83.5%
paper: [http://www.cs.columbia.edu/~polakis/papers/sivakorn_eurosp16.pdf]

SimGAN-Captcha

intro: Solve captcha without manually labeling a training set
github: [https://github.com/rickyhan/SimGAN-Captcha]

手写体识别

High Performance Offline Handwritten Chinese Character Recognition Using GoogLeNet and Directional Feature Maps

arxiv: [http://arxiv.org/abs/1505.04925]
github: [https://github.com/zhongzhuoyao/HCCR-GoogLeNet]

Recognize your handwritten numbers

[https://medium.com/@o.kroeger/recognize-your-handwritten-numbers-3f007cbe46ff#.jllz62xgu]

Handwritten Digit Recognition using Convolutional Neural Networks in Python with Keras

blog: [http://machinelearningmastery.com/handwritten-digit-recognition-using-convolutional-neural-networks-python-keras/]

MNIST Handwritten Digit Classifier

github: [https://github.com/karandesai-96/digit-classifier]

LeNet – Convolutional Neural Network in Python

blog: [http://www.pyimagesearch.com/2016/08/01/lenet-convolutional-neural-network-in-python/]

Scan, Attend and Read: End-to-End Handwritten Paragraph Recognition with MDLSTM Attention

arxiv: [http://arxiv.org/abs/1604.03286]

MLPaint: the Real-Time Handwritten Digit Recognizer

blog: [http://blog.mldb.ai/blog/posts/2016/09/mlpaint/]
github: [https://github.com/mldbai/mlpaint]
demo: [https://docs.mldb.ai/ipy/notebooks/_demos/_latest/Image%20Processing%20with%20Convolutions.html]

Training a Computer to Recognize Your Handwriting

[https://medium.com/@annalyzin/training-a-computer-to-recognize-your-handwriting-24b808fb584#.gd4pb9jk2]

Using TensorFlow to create your own handwriting recognition engine

blog: [https://niektemme.com/2016/02/21/tensorflow-handwriting/]
github: [https://github.com/niektemme/tensorflow-mnist-predict/]

Building a Deep Handwritten Digits Classifier using Microsoft Cognitive Toolkit

blog: [https://medium.com/@tuzzer/building-a-deep-handwritten-digits-classifier-using-microsoft-cognitive-toolkit-6ae966caec69#.c3h6o7oxf]
github: [https://github.com/tuzzer/ai-gym/blob/a97936619cf56b5ed43329c6fa13f7e26b1d46b8/MNIST/minist_softmax_cntk.py]

Hand Writing Recognition Using Convolutional Neural Networks

intro: This CNN-based model for recognition of hand written digits attains a validation accuracy of 99.2% after training for 12 epochs. Its trained on the MNIST dataset on Kaggle.
github: [https://github.com/ayushoriginal/HandWritingRecognition-CNN]

Design of a Very Compact CNN Classifier for Online Handwritten Chinese Character Recognition Using DropWeight and Global Pooling

intro: 0.57 MB, performance is decreased only by 0.91%.
arxiv: [https://arxiv.org/abs/1705.05207]

Handwritten digit string recognition by combination of residual network and RNN-CTC

[https://arxiv.org/abs/1710.03112]

车牌识别

Reading Car License Plates Using Deep Convolutional Neural Networks and LSTMs

arxiv: [http://arxiv.org/abs/1601.05610]

Number plate recognition with Tensorflow

blog: [http://matthewearl.github.io/2016/05/06/cnn-anpr/]
github: [https://github.com/matthewearl/deep-anpr]

end-to-end-for-plate-recognition

github: [https://github.com/szad670401/end-to-end-for-chinese-plate-recognition]

Segmentation-free Vehicle License Plate Recognition using ConvNet-RNN

intro: International Workshop on Advanced Image Technology, January, 8-10, 2017. Penang, Malaysia. Proceeding IWAIT2017
arxiv: [https://arxiv.org/abs/1701.06439]